## Abstract

This chapter describes, in two parts, the methodology proposed for obtaining an approximation of the real option value and of the optimal decision rule for several project investment options by considering technical and market uncertainty. The first part describes the method which approximates the value of a real option using fuzzy numbers to represent technical uncertainties and known stochastic processes to represent market uncertainty (commodity prices), which are used in combination with stochastic simulations (Monte Carlo simulation) so as to reduce the computational time spent on Monte Carlo simulation runs. The second part describes the method for approximating an optimal decision rule and determining the value of a real option for the case where there are several project investment alternatives (options). This method makes use of a genetic algorithm and of known stochastic processes for representing market uncertainty (commodity prices), which are used in combination with stochastic simulations (Monte Carlo simulation) and with variance reduction techniques.

Original language | English |
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Title of host publication | Intelligent Systems in Oil Field Development under Uncertainty |

Editors | Marco A.C. Pacheco, Marley B.R. Vellasco |

Place of Publication | Heidelberg |

Publisher | Springer Berlin |

Pages | 139-186 |

Number of pages | 48 |

ISBN (Print) | 9783540929994 |

DOIs | |

State | Published - 2009 |

Externally published | Yes |

### Publication series

Name | Studies in Computational Intelligence |
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Volume | 183 |

ISSN (Print) | 1860-949X |

### Bibliographical note

Copyright:Copyright 2009 Elsevier B.V., All rights reserved.